Advancement in Additive Manufacturing and Signal Interference Detection in Communication Network

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Circuit and Signal Processing".

Deadline for manuscript submissions: 15 September 2025 | Viewed by 639

Special Issue Editors


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Guest Editor
School of Engineering, Faculty of Science and Engineering, Macquarie University, Sydney, NSW 2109, Australia
Interests: 3D printed antenna; satellite communication; microwave communication; antenna design
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Information and Communication Engineering, Gwangju 61452, Republic of Korea
Interests: metasurface design; mmWave antennas; rain attenuation; antenna design and wave propagation
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Electrical & Data Engineering, University of Technology Sydney, Sydney, NSW 2007, Australia
Interests: antenna design and wave propagation; microwave and millimeter wave communication; engineering electromagnetics; metasurface
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The advancement in communication media are increasing in recent scenario with progress in additive manufacturing and error detection in commuication path. Error detection has been growing concern in defined communication media where the effect can be due to rain especially in higher frequency of operation, signal interference resulted due to unwanted carriers such as Network Termination Devices in satellite and microwave field. In this special issue, we are focusing on the development of novel three dimensional (3D) printed surface along with applicable signal tracing especially focusing on the inference level.  

The topics of interests include but not limited to:

  • Advancement in 5G/B5G/6G technologies;
  • Network Termination Devices management and signal intensity level;
  • Satellite communication path and signal tracing in slant path;
  • Utilization of 3D printed surfaces to detect the error margin;
  • Characterization of novel materials;
  • Use of filaments, resin to realize the complex geometrical surfaces;
  • Ulization of metal 3D printing technologies;
  • Artificial intelligence and use of Neural Network in communication design scenarios;
  • Spectrum Analyzer to detect the interferance level;
  • Use of time division technology for defined time slot;
  • 3D printed beam steerable surface design;
  • Complex array configurable antenna sources;
  • Novel concept for patch design and resonant cavity antenna;
  • Use of copper painted solution on 3D printed antenna surfaces;
  • Ralization of 3D printed sources and its effect on sattellite and microwave communication.

Dr. Sujan Shrestha
Dr. Dong-You Choi
Prof. Dr. Karu P. Esselle
Guest Editors

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Keywords

  • advancement in 5G/B5G/6G technologies
  • network termination devices management and signal intensity level
  • satellite communication path and signal tracing in slant path
  • utilization of 3D printed surfaces to detect the error margin
  • characterization of novel materials
  • use of filaments, resin to realize the complex geometrical surfaces
  • ulization of metal 3D printing technologies
  • artificial intelligence and use of Neural Network in communication design scenarios.
  • spectrum analyzer to detect the interferance level
  • use of time division technology for defined time slot
  • 3D printed beam steerable surface design
  • complex array configurable antenna sources
  • novel concept for patch design and resonant cavity antenna
  • use of copper painted solution on 3D printed antenna surfaces
  • ralization of 3D printed sources and its effect on sattellite and microwave communication

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Published Papers (1 paper)

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Research

13 pages, 2628 KiB  
Article
Indoor Localization Using 6G Time-Domain Feature and Deep Learning
by Chien-Ching Chiu, Hung-Yu Wu, Po-Hsiang Chen, Chen-En Chao and Eng Hock Lim
Electronics 2025, 14(9), 1870; https://doi.org/10.3390/electronics14091870 - 3 May 2025
Viewed by 259
Abstract
Accurate indoor localization is essential for Internet of Things (IoT) systems and autonomous navigation in the 6G communication system. However, achieving precision in environments affected by signal multipath effects and interference remains a challenge for 6G communication systems. We employ a Residual Neural [...] Read more.
Accurate indoor localization is essential for Internet of Things (IoT) systems and autonomous navigation in the 6G communication system. However, achieving precision in environments affected by signal multipath effects and interference remains a challenge for 6G communication systems. We employ a Residual Neural Network (ResNet) augmented with channel and spatial attention mechanisms to enhance indoor localization performance using time-domain data. Through extensive experimentation, our models, when equipped with an attention mechanism, can achieve accurate location under 20% interference. Numerical results show that the ResNet with a Channel Local Attention Block (CLAB) can reduce the localization error by about 12% even when the interference is high. Similarly, the ResNet with a Spatial Local Attention Block (SLAB) can also improve the localization accuracy. While a ResNet combining both CLAB and SLAB can reduce the position error to about 7 cm. Full article
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